Triple

T4330503
Position Surface form Disambiguated ID Type / Status
Subject Aladdin (2019 film) E96736 entity
Predicate producer P490 FINISHED
Object Dan Lin E83863 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Dan Lin | Statement: [Aladdin (2019 film), producer, Dan Lin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dan Lin
Context triple: [Aladdin (2019 film), producer, Dan Lin]
  • A. Dan Lin chosen
    Dan Lin is a Taiwanese-American film producer and executive known for overseeing major franchises such as The Lego Movie series and various DC and Sherlock Holmes films.
  • B. Greg Yaitanes
    Greg Yaitanes is an American television director and producer known for his work on high-profile series such as House of the Dragon and House.
  • C. Dan Goor
    Dan Goor is an American television writer and producer best known for co-creating the comedy series "Brooklyn Nine-Nine" and his work on shows like "Parks and Recreation."
  • D. Chris Yeh
    Chris Yeh is an entrepreneur, investor, and author best known for co-authoring the business strategy book "Blitzscaling" with Reid Hoffman.
  • E. Domee Shi
    Domee Shi is a Chinese-Canadian filmmaker and animator at Pixar best known for directing the feature film "Turning Red" and the Oscar-winning short "Bao."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69b34542fd908190b11b08faad8decfd completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3514c39748190900e13e70ed8848c completed March 12, 2026, 11:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d09fad588190b488012b4fc6cb8c completed March 14, 2026, 9:18 p.m.
Created at: March 12, 2026, 11:13 p.m.